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Some comments on the role of econometrics in economic theory

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  • Martin S. Eichenbaum

Abstract

The basic tension facing econometricians is that structural models are necessary for addressing monetary policy questions. But all models are, by their very nature, false. Econometric programs that focus on testing whether models are true will be ignored by practicing macroeconomists. The critical task facing econometricians is to develop diagnostic tools for assessing the usefulness of models for addressing particular questions. This article reviews two diagnostic strategies.

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  • Martin S. Eichenbaum, 1996. "Some comments on the role of econometrics in economic theory," Economic Perspectives, Federal Reserve Bank of Chicago, vol. 20(Jan), pages 22-31.
    • Handle: RePEc:fip:fedhep:y:1996:i:jan:p:22-31:n:v.20no.1
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    References listed on IDEAS

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    1. Patrick Fève, 1997. "Les méthodes d'étalonnage au regard de l'économétrie," Revue Économique, Programme National Persée, vol. 48(3), pages 629-638.
    2. V. Pandit, 2008. "Structural Modeling under Challenge," Working Papers id:1622, eSocialSciences.
    3. Malley, Jim & Muscatelli, V. Anton, 1999. "Business cycles and productivity growth: Are temporary downturns productive or wasteful?," Research in Economics, Elsevier, vol. 53(4), pages 337-364, December.
    4. Ausloos, Marcel & Jovanovic, Franck & Schinckus, Christophe, 2016. "On the “usual” misunderstandings between econophysics and finance: Some clarifications on modelling approaches and efficient market hypothesis," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 7-14.
    5. Jovanovic, Franck & Schinckus, Christophe, 2016. "Breaking down the barriers between econophysics and financial economics," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 256-266.
    6. V. Pandit, 2001. "Structural Modelling Under Challenge," Working papers 98, Centre for Development Economics, Delhi School of Economics.
    7. Jinho Choi & Juan Carlos Escanciano & Junjie Guo, 2022. "Generalized band spectrum estimation with an application to the New Keynesian Phillips curve," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 1055-1078, August.
    8. Chiarini, Bruno & Piselli, Paolo, 2001. "Identification and dimension of the NAIRU," Economic Modelling, Elsevier, vol. 18(4), pages 585-611, December.
    9. Kevin Hoover & Katarina Juselius, 2012. "Experiments, Passive Observation and Scenario Analysis: Trygve Haavelmo and the Cointegrated Vector Autoregression," Discussion Papers 12-16, University of Copenhagen. Department of Economics.
    10. Engsted, Tom & Schneider, Jesper W., 2023. "Non-Experimental Data, Hypothesis Testing, and the Likelihood Principle: A Social Science Perspective," SocArXiv nztk8, Center for Open Science.
    11. Ormerod, Paul, 2002. "The US business cycle: power law scaling for interacting units with complex internal structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 314(1), pages 774-785.
    12. Berkowitz, Jeremy, 2001. "Generalized spectral estimation of the consumption-based asset pricing model," Journal of Econometrics, Elsevier, vol. 104(2), pages 269-288, September.
    13. Pedro Garcia Duarte & Kevin D. Hoover, 2012. "Observing Shocks," History of Political Economy, Duke University Press, vol. 44(5), pages 226-249, Supplemen.
    14. Duo Qin, 2022. "Redirect the Probability Approach in Econometrics Towards PAC Learning," Working Papers 249, Department of Economics, SOAS University of London, UK.
    15. Jovanovic, Franck & Schinckus, Christophe, 2017. "Econophysics and Financial Economics: An Emerging Dialogue," OUP Catalogue, Oxford University Press, number 9780190205034.
    16. Ossama Mikhail, 2005. "What Happens After A Technology Shock? A Bayesian Perspective," Macroeconomics 0510016, University Library of Munich, Germany.

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